# Direct outputs eligible for public release

# GLOBAL SETTINGS --------------------------------------------------------------

options(
  scipen = 999,
  digits = 16,
  max.print = .Machine$integer.max,
  show.error.locations = TRUE,
  warn = 1
)

RNGkind("L'Ecuyer-CMRG")
seed <- 818675309L
set.seed(seed) # setting main seed

# PACKAGES ---------------------------------------------------------------------
library(data.table)
library(ggplot2)
library(scales)

# PACKAGE SETTINGS -------------------------------------------------------------

# data.table
setDTthreads(threads = 1L)
options(datatable.print.class = TRUE, datatable.print.keys = TRUE)
# so that printing the data.table also shows the variable type on top

# BEGIN FILE -------------------------------------------------------------------

outcome <- "db_w2_wages"

# Read in all estimates

fd_cohort_coefs <-
    setDT(
        readRDS("~/estimation-output/single-cohort-fd-results.rds")
        )[
            estimate_type == "coefficient",
            .(event_time, estimate)
        ]

fd_pooled_coefs <-
    setDT(
        readRDS("~/estimation-output/pooled-fd-results.rds")
        )[
            estimate_type == "coefficient",
            .(event_time, estimate)
        ]

did_laterwinners_coefs <-
    readRDS(
        sprintf("~/estimation-output/event_study_estimates_%s.rds", outcome)
    )

did_laterwinners_coefs <- setDT(did_laterwinners_coefs[[1]])

did_laterwinners_coefs <-
    did_laterwinners_coefs[
        between(ref_event_time, -7L, 5L, incbounds = TRUE) &
        ref_onset_time == "Cohort-Weighted" &
        model == "reduced_form" &
        rn == "att",
        .(
            ref_event_time,
            estimate,
            cluster_se
        )
    ]

# Introduce a omitted_event_time row
did_laterwinners_coefs <-
    rbindlist(
        list(
            did_laterwinners_coefs,
            data.table(
                ref_event_time = -2L,
                estimate = 0,
                cluster_se = 0
            )
        ),
        use.names = TRUE
    )
setorderv(did_laterwinners_coefs, "ref_event_time")

did_nonwinners_coefs <-
    readRDS(
        sprintf(
        "~/estimation-output/event_study_estimates_%s_nonwinner_control_group.rds", #nolint
        outcome
        )
    )

did_nonwinners_coefs <- setDT(did_nonwinners_coefs[[1]])

did_nonwinners_coefs <-
    did_nonwinners_coefs[
        between(ref_event_time, -7L, 5L, incbounds = TRUE) &
        ref_onset_time == "Cohort-Weighted" &
        model == "reduced_form" &
        rn == "att",
        .(
            ref_event_time,
            estimate,
            cluster_se
        )
    ]

# Introduce a omitted_event_time row
did_nonwinners_coefs <-
    rbindlist(
        list(
            did_nonwinners_coefs,
            data.table(
                ref_event_time = -2L,
                estimate = 0,
                cluster_se = 0
            )
        ),
        use.names = TRUE
    )
setorderv(did_nonwinners_coefs, "ref_event_time")

# Label and combine estimates

fd_cohort_coefs[, cluster_se := 0]
fd_cohort_coefs[, estimate_label := "FD (Single Cohort)"]

fd_pooled_coefs[, cluster_se := 0]
fd_pooled_coefs[, estimate_label := "FD (Pooled)"]

did_laterwinners_coefs[, estimate_label := "DiD (Later Winners)"]
setnames(did_laterwinners_coefs, "ref_event_time", "event_time")

did_nonwinners_coefs[, estimate_label := "DiD (Non-Winners)"]
setnames(did_nonwinners_coefs, "ref_event_time", "event_time")

all_specs <-
    rbindlist(
        list(
            fd_cohort_coefs,
            fd_pooled_coefs,
            did_laterwinners_coefs,
            did_nonwinners_coefs
        ),
        use.names = TRUE
    )
all_specs[
    ,
    estimate_label :=
        factor(
            estimate_label,
                levels = c(
                    "FD (Single Cohort)",
                    "FD (Pooled)",
                    "DiD (Later Winners)",
                    "DiD (Non-Winners)"
                    )
        )
]
all_specs[estimate_label != "DiD (Later Winners)", cluster_se := 0]

# Produce Figure 3.2 - comparison of Figure 3.1 estimates altogether

figure_3_2 <-
    ggplot(
        aes(x = event_time, y = estimate, color = factor(estimate_label)),
        data = all_specs[between(event_time, -7L, 5L, incbounds = TRUE)]
    ) +
    geom_line() +
    geom_ribbon(
        aes(
            ymin = estimate - (1.64 * cluster_se),
            ymax = estimate + (1.64 * cluster_se)
        ),
        linetype = 0,
        alpha = 0.2,
        show.legend = FALSE
    ) +
    theme_bw(base_size = 13) +
    theme(panel.grid.minor = element_blank()) +
    scale_x_continuous(
        breaks = seq.int(from = -7L, to = 5L, by = 1L),
        expand = expansion(mult = c(0.0025, 0.0025))
    ) +
    scale_y_continuous(breaks = breaks_extended(n = 10)) +
    labs(x = "Event Time (ℓ)", y = "Estimate (2016 USD)") +
    theme(
        legend.title = element_blank(),
        legend.position = c(0.159, 0.1525),
        legend.background = element_rect(fill = "white", color = "grey"),
        strip.text.x = element_blank(),
        strip.background = element_blank(),
        legend.key = element_rect(NA),
        legend.spacing.y = unit(2, "mm"),
        legend.key.height = unit(4, "mm"),
        legend.key.width = unit(4, "mm"),
        legend.margin = margin(t = 0, r = 0.1, b = 0.15, l = 0.1, unit = "cm")
    ) +
    scale_color_viridis_d() +
    guides(color = guide_legend(ncol = 1, byrow = TRUE)) +
    coord_cartesian(ylim = c(-5000, 500))

ggsave(
    plot = figure_3_2,
    filename = "~/paper/figures/figure-3.2.png",
    width = 6,
    height = 4,
    dpi = 600
)

ggsave(
    plot = figure_3_2,
    filename = "~/paper/figures/figure-3.2.tif",
    width = 6,
    height = 4,
    device = "tiff",
    dpi = 600
)

# Housekeeping
outcome <- NULL
fd_cohort_coefs <- NULL
fd_pooled_coefs <- NULL
did_laterwinners_coefs <- NULL
did_nonwinners_coefs <- NULL
all_specs <- NULL
figure_3_2 <- NULL
rm(
    outcome,
    fd_cohort_coefs,
    fd_pooled_coefs,
    did_laterwinners_coefs,
    did_nonwinners_coefs,
    all_specs,
    figure_3_2
)
